Network analysis of 2-mode data

Network analysis is distinguished from traditional social science by the dyadic nature of the standard data set. Whereas in traditional social science we study monadic attributes of individuals, in network analysis we study dyadic attributes of pairs of individuals. These dyadic attributes (e.g. social relations) may be represented in matrix form by a square 1-mode matrix. In contrast, the data in traditional social science are represented as 2-mode matrices. However, network analysis is not completely divorced from traditional social science, and often has occasion to collect and analyze 2-mode matrices. Furthermore, some of the methods developed in network analysis have uses in analysing non-network data. This paper presents and discusses ways of applying and interpreting traditional network analytic techniques to 2-mode data, as well as developing new techniques. Three areas are covered in detail: displaying 2-mode data as networks, detecting clusters and measuring centrality.

Sports programs of the Spanish radio in the social network Facebook: compared study (2010-2015)

Social networks have increasingly become a showcase where the media can be promoted. Like many other media, radio stations have made use of social networks to promote themselves in a better way and, sometimes, to keep more feedback with their listeners. But not all programs make the same use and not all of them have managed to reach in the same way his followers. This article discusses the consolidation in the social networks of the major radio sports programs in Spain. Through a comparative analysis between 2010 and 2015, throughout the text, the authors have tried to observe the evolution of the programs and, at the same time, to establish comparisons between the followers that these programs have on social networks and the number of listeners as EGM.

"Thematically Analysing Social Network Content During Disasters Through the Lens of the Disaster Management Lifecycle" & "Investigating Similarity Between Privacy Policies of Social Networking Sites as a Precursor for Standardization"

Abstract 1: Social Networks such as Twitter are often used for disseminating and collecting information during natural disasters. The potential for its use in Disaster Management has been acknowledged. However, more nuanced understanding of the communications that take place on social networks are required to more effectively integrate this information into the processes within disaster management. The type and value of information shared should be assessed, determining the benefits and issues, with credibility and reliability as known concerns. Mapping the tweets in relation to the modelled stages of a disaster can be a useful evaluation for determining the benefits/drawbacks of using data from social networks, such as Twitter, in disaster management.A thematic analysis of tweets’ content, language and tone during the UK Storms and Floods 2013/14 was conducted. Manual scripting was used to determine the official sequence of events, and classify the stages of the disaster into the phases of the Disaster Management Lifecycle, to produce a timeline. Twenty- five topics discussed on Twitter emerged, and three key types of tweets, based on the language and tone, were identified. The timeline represents the events of the disaster, according to the Met Office reports, classed into B. Faulkner’s Disaster Management Lifecycle framework. Context is provided when observing the analysed tweets against the timeline. This illustrates a potential basis and benefit for mapping tweets into the Disaster Management Lifecycle phases. Comparing the number of tweets submitted in each month with the timeline, suggests users tweet more as an event heightens and persists. Furthermore, users generally express greater emotion and urgency in their tweets.This paper concludes that the thematic analysis of content on social networks, such as Twitter, can be useful in gaining additional perspectives for disaster management. It demonstrates that mapping tweets into the phases of a Disaster Management Lifecycle model can have benefits in the recovery phase, not just in the response phase, to potentially improve future policies and activities. Abstract2: The current execution of privacy policies, as a mode of communicating information to users, is unsatisfactory. Social networking sites (SNS) exemplify this issue, attracting growing concerns regarding their use of personal data and its effect on user privacy. This demonstrates the need for more informative policies. However, SNS lack the incentives required to improve policies, which is exacerbated by the difficulties of creating a policy that is both concise and compliant. Standardization addresses many of these issues, providing benefits for users and SNS, although it is only possible if policies share attributes which can be standardized. This investigation used thematic analysis and cross- document structure theory, to assess the similarity of attributes between the privacy policies (as available in August 2014), of the six most frequently visited SNS globally. Using the Jaccard similarity coefficient, two types of attribute were measured; the clauses used by SNS and the coverage of forty recommendations made by the UK Information Commissioner’s Office. Analysis showed that whilst similarity in the clauses used was low, similarity in the recommendations covered was high, indicating that SNS use different clauses, but to convey similar information. The analysis also showed that low similarity in the clauses was largely due to differences in semantics, elaboration and functionality between SNS. Therefore, this paper proposes that the policies of SNS already share attributes, indicating the feasibility of standardization and five recommendations are made to begin facilitating this, based on the findings of the investigation.

Automated organizational network analysis for enterprise 2.0

Social Networking Sites have recently become a mainstream communications technology for many people around the world. Major IT vendors are releasing social software designed for use in a business/commercial context. These Enterprise 2.0 technologies have impressive collaboration and information sharing functionality, but so far they do not have any organizational network analysis (ONA) features that reveal any patterns of connectivity within business units. This paper shows the impact of organizational network analysis techniques and social networks on organizational performance, we also give an overview on current enterprise social software, and most importantly, we highlight how Enterprise 2.0 can help automate an organizational network analysis.

Bridging the gap between research and practice in organizational network analysis: a conversation between Rob Cross and Martin Kilduff

The article features a conversation between Rob Cross and Martin Kilduff about organizational network analysis in research and practice. It demonstrates the value of using social network perspectives in HRM. Drawing on the discussion about managing personal networks; managing the networks of others; the impact of social networking sites on perceptions of relationships; and ethical issues in organizational network analysis, we propose specific suggestions to bring social network perspectives closer to HRM researchers and practitioners and rebalance our attention to people and to their relationships.

A survey of data mining techniques for social media analysis

Social network has gained remarkable attention in the last decade. Accessing social network sites such as Twitter, Facebook LinkedIn and Google+ through the internet and the web 2.0 technologies has become more affordable. People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters. The heavy reliance on social network sites causes them to generate massive data characterised by three computational issues namely; size, noise and dynamism. These issues often make social network data very complex to analyse manually, resulting in the pertinent use of computational means of analysing them. Data mining provides a wide range of techniques for detecting useful knowledge from massive datasets like trends, patterns and rules [44]. Data mining techniques are used for information retrieval, statistical modelling and machine learning. These techniques employ data pre-processing, data analysis, and data interpretation processes in the course of data analysis. This survey discusses different data mining techniques used in mining diverse aspects of the social network over decades going from the historical techniques to the up-to-date models, including our novel technique named TRCM. All the techniques covered in this survey are listed in the Table.1 including the tools employed as well as names of their authors.

Forum: social network for the surveillance and prevention of workplace accidents

In 2008, academic researchers and public service officials created a university extension studies platform based on online and on-site meetings denominated "Work-Related Accidents Forum: Analysis, Prevention, and Other Relevant Aspects. Its aim was to help public agents and social partners to propagate a systemic approach that would be helpful in the surveillance and prevention of work-related accidents. This article describes and analyses such a platform. Online access is free and structured to: support dissemination of updated concepts; support on-site meetings and capacity to build educational activities; and keep a permanent space for debate among the registered participants. The desired result is the propagation of a social-technical-systemic view of work-related accidents that replaces the current traditional view that emphasizes human error and results in blaming the victims. The Forum uses an educational approach known as permanent health education, which is based on the experience and needs of workers and encourages debate among participants. The forum adopts a problematizing pedagogy that starts from the requirements and experiences of the social actors and stimulates support and discussions among them in line with an ongoing health educational approach. The current challenge is to turn the platform into a social networking website in order to broaden its links with society.

Scientific collaboration network among Brazilian universities: an analysis in Dentistry area

This paper analyses the scientific collaboration network formed by the Brazilian universities that investigate in dentistry area. The constructed network is based on the published documents in the Scopus (Elsevier) database covering a period of 10 (ten) years. It is used social network analysis as the best methodological approach to visualize the capacity for collaboration, dissemination and transmission of new knowledge among universities. Cohesion and density of the collaboration network is analyzed, as well as the centrality of the universities as key-actors and the occurrence of subgroups within the network. Data were analyzed using the software UCINET and NetDraw. The number of documents published by each university was used as an indicator of its scientific production.

Forum: social network for the surveillance and prevention of workplace accidents

In 2008, academic researchers and public service officials created a university extension studies platform based on online and on-site meetings denominated "Work-Related Accidents Forum: Analysis, Prevention, and Other Relevant Aspects. Its aim was to help public agents and social partners to propagate a systemic approach that would be helpful in the surveillance and prevention of work-related accidents. This article describes and analyses such a platform. Online access is free and structured to: support dissemination of updated concepts; support on-site meetings and capacity to build educational activities; and keep a permanent space for debate among the registered participants. The desired result is the propagation of a social-technical-systemic view of work-related accidents that replaces the current traditional view that emphasizes human error and results in blaming the victims. The Forum uses an educational approach known as permanent health education, which is based on the experience and needs of workers and encourages debate among participants. The forum adopts a problematizing pedagogy that starts from the requirements and experiences of the social actors and stimulates support and discussions among them in line with an ongoing health educational approach. The current challenge is to turn the platform into a social networking website in order to broaden its links with society.

Gli assetti dipartimentali ospedalieri tra strutture formali e organizzazione informale

Il confronto in corso tra gli esperti di management sanitario sui dipartimenti ospedalieri, la crescente attenzione sui modelli di organizzazione a rete e le indagini sui servizi sanitari condotte con strumenti di analisi dei network hanno rappresentato la base su cui sviluppare il disegno dello studio. La prospettiva relazionale e le tecniche di social network analysis (Sna) sono state impiegate in un indagine empirica effettuata presso tre Dipartimenti Ospedalieri dell’Azienda USL di Bologna per osservare la struttura delle relazioni che intercorrono nell’ambito dei dipartimenti, tra le unità operative e tra i clinici, al fine di assicurare il quotidiano svolgersi dei processi clinico assistenziali dei pazienti. L’indagine si è posta tre obiettivi. Il primo è quello di confrontare la rete delle relazioni “reali” che intercorrono tra unità operative e tra clinici con le relazioni “progettate” attraverso l’afferenza delle unità operative nei dipartimenti e dei singoli clinici nelle unità operative. In sostanza si tratta di confrontare, con intenti esclusivamente conoscitivi, la struttura organizzativa formale – istituzionale con quella “informale”, che emerge dalle relazioni giornaliere tra i professionisti. In secondo luogo si intende comprendere se e come i fattori di natura attributiva che caratterizzano i singoli rispondenti, (es. età, sesso, laurea, anni di permanenza in azienda, ecc.) incidano sulla natura e sull’intensità delle relazioni e delle collaborazioni intrattenute con i colleghi all’interno dell’azienda. L’analisi ha un intento “esplicativo”, in quanto si cerca di indagare come le similitudini nelle caratteristiche individuali possano o meno incidere sull’intensità degli scambi e quindi delle collaborazioni tra professionisti. Il terzo obiettivo è volto a comprendere se e come i fattori attributivi e/o relazionali siamo in grado di spiegare l’attitudine mostrata dai singoli professionisti rispetto l’adozione di un approccio alla pratica clinica ispirato all’Evidence based medicine. Lo scopo è quello di verificare se la disponibilità / orientamento ad operare in una prospettiva evidence based sia più legata ad elementi e caratteristiche personali piuttosto che all’influenza esercitata da coloro con i quali si entra in contatto per motivi lavorativi. La relativa semplicità della fase di indagine ha indotto ad arricchire i contenuti e gli obiettivi originari del lavoro allo scopo di correlare indicatori relazionali e attributivi con indicatori di “performance”, in particolare di efficienza e appropriatezza. Le relazioni sono state rilevate attraverso un questionario sociometrico inserito in uno spazio web accessibile dalla rete ospedaliera e compilato online da parte dei medici. Il questionario è stato organizzato in tre sezioni: la prima per la raccolta di informazioni anagrafiche e dati attributivi dei clinici; la seconda volta a raccogliere i dati relazionali, funzionali e di consulenza, verso le equipe di professionisti (unità operative) e verso i singoli colleghi clinici; la terza sezione è dedicata alla raccolta di informazioni sull’utilizzo delle evidenze scientifiche a supporto della propria pratica clinica (consultazione di riviste, banche dati, rapporti di HTA, etc,) e sulla effettiva possibilità di accesso a tali strumenti. L’azienda ha fornito i dati di struttura e la base dati degli indicatori di attività delle UO arruolate nello studio. La compliance complessiva per i tre dipartimenti è stata pari a circa il 92% (302 rispondenti su un campione di 329 medici.). Non si sono rilevate differenze significative sulla compliance per i tre dipartimenti considerati. L’elaborazione dei dati è stata effettuata mediante specifici software per l’analisi delle reti sociali, UCINET 6 per il calcolo degli indicatori relazionali (centralità, densità, structural holes etc.), e Pajek per l’analisi grafica dei network. L’ultima fase è stata realizzata con l’ausilio del software statistico STATA vers. 10. L’analisi dei risultati è distinta in due 2 fasi principali. In primis è stato descritto il network di relazioni professionali rilevate, sono stai calcolati i relativi indicatori di centralità relazionale e verificato il grado di sovrapposizione tra struttura formale dei dipartimenti in studio con le relazioni informali che si stabiliscono tra di essi nell’ambito clinico. Successivamente è stato analizzato l’impatto che le relazioni esercitano sulla propensione da parte dei singoli medici a utilizzare nuove evidenze scientifiche I primi risultati emersi dallo studio forniscono interessanti evidenze, con particolare riguardo al dato di un discreto grado di “sovrapposizione” tra struttura formale e informale delle unità organizzative in studio e a correlazioni significative tra fattori relazionali e attitudine dei medici verso l’utilizzo dell’approccio EBM. Altre evidenze, in specie la correlazione tra “centralità” degli attori organizzativi e alcuni indicatori di performance /appropriatezza, meritano ulteriori approfondimenti e una definitiva validazione. In conclusione lo studio dimostra che la prospettiva relazionale e la Sna consentono di porre in evidenza caratteristiche dei dipartimenti, dei suoi attori e delle loro reti di reciproche relazioni, in grado di favorire la comprensione di alcune dinamiche ricercate proprio attraverso l’organizzazione dipartimentale e quindi di specifico interesse per il management, i clinici e quanti altri impegnati nella gestione e nello sviluppo di questo modello di organizzazione dell’ospedale.

Business analytics e risorse umane. Il caso dell'azienda CAE S.P.A.

La velocità di cambiamento che caratterizza il mercato ha posto l'attenzione di molte imprese alla Business Analysis. La raccolta, la gestione e l'analisi dei dati sta portando numerosi benefici in termini di efficienza e vantaggio competitivo. Questo è reso possibile dal supporto reale dei dati alla strategia aziendale. In questa tesi si propone un'applicazione della Business Analytics nell'ambito delle risorse umane. La valorizzazione del Capitale Intellettuale è fondamentale per il miglioramento della competitività dell'impresa, favorendo così la crescita e lo sviluppo dell'azienda. Le conoscenze e le competenze possono incidere sulla produttività, sulla capacità innovativa, sulle strategie e sulla propria reattività a comprendere le risorse e le potenzialità a disposizione e portano ad un aumento del vantaggio competitivo. Tramite la Social Network Analysis si possono studiare le relazioni aziendali per conoscere diversi aspetti della comunicazione interna nell'impresa. Uno di questi è il knowledge sharing, ovvero la condivisione della conoscenza e delle informazioni all'interno dell'organizzazione, tema di interesse nella letteratura per via delle potenzialità di crescita che derivano dal buon utilizzo di questa tecnica. L'analisi si è concentrata sulla mappatura e sullo studio del flusso di condivisione di due delle principali componenti della condivisione di conoscenza: sharing best prectices e sharing mistakes, nel caso specifico si è focalizzato lo studio sulla condivisione di miglioramenti di processo e di problematiche o errori. È stata posta una particolare attenzione anche alle relazioni informali all'interno dell'azienda, con l'obiettivo di individuare la correlazione tra i rapporti extra-professionali nel luogo di lavoro e la condivisione di informazioni e opportunità in un'impresa. L'analisi delle dinamiche comunicative e l'individuazione degli attori più centrali del flusso informativo, permettono di comprendere le opportunità di crescita e sviluppo della rete di condivisione. La valutazione delle relazioni e l’individuazione degli attori e delle connessioni chiave fornisce un quadro dettagliato della situazione all'interno dell'azienda.

Reti di partecipazione fra società di capitale in Italia: presenza di topologie caratterizzate da distribuzioni power law

Quando la probabilità di misurare un particolare valore di una certa quantità varia inversamente come potenza di tale valore, il quantitativo è detto come seguente una power-law, conosciuta anche come legge di Zipf o distribuzione di Pareto. Obiettivo di questa tesi sarà principalmente quello di verificare se il campione esteso di imprese segue la power-law (e se sì, in che limiti). A tale fine si configureranno i dati in un formato di rete monomodale, della quale si studieranno alcune macro-proprietà di struttura a livllo complessivo e con riferimento alle componenti (i singoli subnet distinti) di maggior dimensione. Successivamente si compiranno alcuni approfondimenti sulla struttura fine di alcuni subnet, essenzialmente rivolti ad evidenziare la potenza di unapproccio network-based, anche al fine di rivelare rilevanti proprietà nascoste del sistema economico soggiacente, sempre, ovviamente, nei limiti della modellizzazione adottata. In sintesi, ciò che questo lavoro intende ottenere è lo sviluppo di un approccio alternativo al trattamento dei big data a componente relazionale intrinseca (in questo caso le partecipazioni di capitale), verso la loro conversione in "big knowledge": da un insieme di dati cognitivamente inaccessibili, attraverso la strutturazione dell'informazione in modalità di rete, giungere ad una conoscenza sufficientemente chiara e giustificata.

The scholarly networks of Albrecht von Haller and the Economic Society of Bern – a multi-level network analysis

Here, by the example of the transfer of cultivated plants in the context of the correspondence networks of Albrecht von Haller and the Economic Society, a multi-level network analysis is suggested. By a multi-level procedure, the chronological dynamics, the social structure, the spatial distribution and the functional networking are analyzed one after the other. These four levels of network analysis do not compete with each other but are mutually supporting. This aims at a deeper understanding of how these networks contributed to an international transfer of knowledge in the 18th century.

Social network size and perceived network sufficiency as predictors of perceived health status

This study focused on the relationship between social network size (number of friends and relatives), perceived sufficiency of the network and self-rated health utilizing data from the National Survey of Personal Health Practices and Consequences, 1979. For men neither perceived sufficiency nor number of relatives were associated with self-rated health status. The number of friends was positively associated with health status. For women perceived network sufficiency was positively and significantly related to health status, independent of network size. The number of friends and relatives was not associated with self-rated health status. The sociodemographic variables accounted for most of the explained variance in health status for both males and females. Social networks may hold different meanings for women and men, and may require qualitative as well as quantitative analysis. There may have been insufficient variance in the major variables to produce meaningful results. ^